Study On Adaptive Resource Allocation Algorithm In Multiuser OFDM System

1. IntroductionRecently, with the improvement of people's living standards, people are increasingly demanding on mobile communications business. Voice alone can not meet people's needs, high-speed data services and multimedia services have become the dominant business in modern mobile communication systems. Therefore, modern mobile communication systems must be able to provide high-speed and highly reliable communication services. However, the spectrum resources in mobile communication systems are limited, and the complexity of the mobile communication environment will seriously affect the performance of the systems. Therefore, to achieve high quality communication services is very challenging problem. Orthogonal frequency division multiplexing (OFDM) technology which is a unique multi-carrier modulation technique and has a very high spectral efficiency and strong anti-inter-symbol interference capability is regarded as the preferred technology of modern communication. In addition, the technology of OFDM dynamic resource allocation can adjust the sub-carriers, bit or power allocation according to the instantaneous channel state. Thus, it can improve system performance and further the efficiency of spectrum utilization.The dynamic resource allocation technique for OFDM systems is mainly based on two criteria, one is the margin adaptive (MA), which is to minimize total transmission power under the constraints of user's rate and bit error rate. Another is the rate adaptive (RA), which is to maximize the total transmission rate of system under the constraints of total power and bit error rate.In this paper, the dynamic resource allocation algorithms based on RA criteria are studied. The proportional fairness among users is considered when meeting the RA criteria. This problem was first analyzed in [45], although the algorithm proposed in [45] achieved maximum capacity and proportional fairness among users. In order to achieve power allocation among users, nonlinear equations must be solved, which increased the computational complexity of the algorithm. In [49], a concept that the number of carriers assigned to user is proportional to the scale factor of user's rate was introduced. And the power allocation problem was converted into solving linear equations which reduced computational complexity. But this algorithm may not be able to meet the fairness among users. Aiming at the above problems, a new adaptive resource allocation algorithm based on fairness threshold is proposed in this paper. In the process of sub-carrier allocation, the fairness threshold can achieve rough tradeoff between capacity and fairness. Then power allocation base on Particle Swarm Optimization (PSO) is introduced to realize required fairness.2. Improved multiuser dynamic resource allocation algorithm for OFDM systemsThis paper presents a novel resource allocation algorithm, which introduces a concept of fairness threshold. The algorithm is a suboptimal algorithm in which carrier allocation and power allocation are considered separately. In the process of sub-carrier allocation, first, that power is equally distributed to each carrier is assumed. Then the fairness among users is calculated. If the fairness is greater than the fairness threshold, the sub-carrier with the largest channel gain is distributed to the appropriate user so that system can achieve maximum capacity. If the fairness is less than the fairness threshold, the user with minimum proportional rate has priority to choose the sub-carrier so that the maximum fairness among users is achieved. After the sub-carrier allocation, the power allocation is studied. Since the solution to the power distribution is a nonlinear constraint optimization problem, a penalty function is applied to transform this problem into a non-restricted optimization problem, so that this problem is solved by using particle swarm optimization (PSO), finally, fairness among users is achieved.3. Simulation results and performance analysisThe simulations show that the proposed algorithm can make good use of fairness threshold to quantify tradeoff between capacity and fairness. After the carrier allocation, the capacity of system already has been improved. The smaller the value of fairness threshold, the better the performance, and the performance may exceed those of the algorithms proposed in [45] and [49]. The carrier allocation fairness among users is only a rough implementation. Thus power allocation is applied to adjust the fairness. After the power allocation, the fairness among users has been achieved, even though the capacity somewhat decrease, the performance is better than those of the algorithms proposed in [45] and [49], and PSO algorithm also has a fast convergence.